Detection of infections in liquid samples by detecting fatty acids present in the headspace associated with the liquid sample

ABSTRACT

A method for detecting the presence of an infection in a liquid sample comprising the steps of: lowering the pH of the liquid sample so as to drive fatty acids present in the liquid sample to the gaseous phase; detecting fatty acids, ammonia and, optionally amine species present as gases in a headspace associated with the liquid sample using a detector which is sensitive to the presence of fatty acids, ammonia and, optionally, amine species; and correlating the presence of detected fatty acids, ammonia and, optionally, amine species with the presence of the infection.

[0001] This invention relates to the detection of the presence of aninfection in a liquid sample using a gas detector, with particular, butby no means exclusive, reference to the detection of urinary tractinfection.

[0002] It is known from the applicant's International Application No. WO95/33848 that microorganisms can be detected using arrays of gas sensorsto detect characteristic gases or vapours produced by themicroorganisms. An example of such an array is an array ofsemiconducting organic polymer gas sensors. The applicant'sInternational Applications Nos. WO 98/29563 and WO 98/39470 describefurther aspects and refinements to the technique, and relateddevelopments. In general, the approach with arrays of gas sensors is toutilise a large number (twenty, thirty or more) of different gas sensorswhich possesses different but overlapping sensitivities towardsdifferent gaseous species (so-called “electronic noses”). Gases arerecognised from the characteristic “fingerprint” or pattern of responseacross the array. However, detection can be difficult in a complexsystem having mixed populations of microflora and microfaunae and/orsystems in which many volatile species are present.

[0003] There are more than two hundred different volatile organiccompounds present in human uninfected urine. Although it is known to bea possibility that urine from patients with urinary tract infections mayhave a characteristic profile of volatile organic compounds due to thepresence of distinctive bacterial metabolites, previous work in thisarea has not lead to a practical application of this method.

[0004] Manja and Rao (J. Clin. Microbiol. 17 (1983) 264) performedconventional gas-liquid chromatography (GLC) on urine samples incubatedwith appropriate supplements and showed that the E. coli could beidentified by the production of ethanol from lactose, and Klebsiellaspecies by the production of ethanol from adonitol. Hayward andcolleagues (J. Clin. Microbiol., 6 (1977) 195; J. Clin. Microbiol., 6(1977) 202; J. Chromatogr., 274 (1983) 27; J. Chromatogr., 307 (1984)11)utilised head space gas-liquid chromatography (HS-GLC) to identifyvolatile bacterial metabolites in artificial cultures and urine. Proteusspecies characteristically produced dimethyl disulfide and methylmercaptan from L-methionine, and trimethylamine from acetylcholine; E.coli and other coliforms produced ethanol from lactose or arabinose.This system was moderately successful in distinguishing infected anduninfected urine by direct analysis, but better results were obtainedafter incubating with arabinose and acetylcholine. Barrett et al (J.Clin. Pathol. 31(9) (1978) 859) used gas liquid chromatography toanalyse clinically infected urines. Acetic acid was the only compoundfound consistently and it enabled 10⁶ microorganisms per ml to bedetected. However, urinary tract infection is diagnosed by the presenceof 10⁵ organisms per ml or more, and thus the authors concluded thattheir method was insufficiently sensitive for the detection ofbacteriurea. Furthermore, Pseudomonas aeruginosa and Candida albicanswere not detectable at all.

[0005] None of the work described above in the area of urinary tractinfection has led to a practical detection method. It is possible thatthis failure is due to one or more of the following reasons: a lack ofinstrument sensitivity; failure to discriminate complex volatilemixtures; and failure to identify suitable “marker” volatiles, which arereliably indicative of infection.

[0006] The present invention overcomes the above-mentioned problems anddifficulties, and provides a quick, reliable and practical screeningtechnique for the detection of urinary tract infection (UTI). Thetechnique is easily automated and may be performed by unskilledoperatives with a minimum of technical back-up. It will become apparentthat the technique may be applicable to the detection of otherinfections as well.

[0007] For the avoidance of doubt, the terms “gas” and “gases” areunderstood to embrace all species present in the gas phase, includingvolatile species emanating from liquids and sublimed species emanatingfrom solids.

[0008] According to the invention there is provided a method fordetecting the presence of an infection in a liquid sample comprising thesteps of:

[0009] lowering the pH of the liquid sample so as to drive fatty acidspresent in the liquid sample into the gaseous phase;

[0010] detecting fatty acids, ammonia and, optionally, amine speciespresent as gases in a headspace associated with the liquid sample usinga detector which is sensitive to the present of fatty acids, ammoniaand, optionally, amine species; and

[0011] correlating the presence of the detected fatty acids, ammoniaand, optionally, amine species with the presence of the infection.

[0012] Surprisingly, this relatively small set of “marker” species hasbeen found to be indicative of a range of infections, and has enabledthe provision of a detection technique having the aforesaid advantages.Furthermore, it is surprising that ammonia (and/or amine marker species)can be detected with sufficient sensitivity despite the acidification ofthe source.

[0013] The liquid sample may be, or may be derived from, a body fluid.The infection may be a urinary tract infection and the liquid sample maybe, or may be derived from, a urine sample. However, it is possible thatother infections may be detected using the “markers” disclosed above.

[0014] Infection by any of the microorganisms Proteus mirabilis,Staphylococcus aureus, Staphylococcus saprophyticus, Eschericia coli,Klebsiella pneumoniae and Enterdcoccus faecalis may be detectable.

[0015] The detector may be sensitive to gaseous acetic acid, and thepresence of acetic acid, ammonia and, optionally, amine species may becorrelated with the presence of the infection. Acetic acid has beenfound to be the most important fatty acid marker (ammonia being a moremost important marker than amine species). The detector may comprisesemiconducting organic polymer.

[0016] The detector may comprise an array of gas sensors. An array, inthe context of the present invention, is two or more gas sensors. Incontrast to conventional electronic noses, it has been found that arrayshaving only a small number of physically different gas sensors can beused advantageously. For example, an array may comprise five or fewersensor types which are sensitive to fatty acids, and five or fewersensor types which are sensitive to ammonia (and/or amines). As few asfour different sensor types have been found to be sufficient.

[0017] The array may comprise gas sensors having semiconducting organicpolymer as a gas sensitive layer.

[0018] The detector may comprise at least one conductimetric gas sensorhaving a gas sensitive layer onto which gases absorb and desorp, and inwhich analytes are detected by:

[0019] exposing the gas sensor to the headspace, thereby allowing theadsorption of analytes present in the headspace onto the gas sensitivelayer; and

[0020] making conductimetric measurements of the sensor during adesorption phase in which there is nett desorption of analyte from thegas sensitive layer. This approach has been found to be extremelyadvantageous in terms of improving sensitivity and reproducibility. Theprincipal reason for this is that the effect of water vapour appears tobe substantially eliminated in the desorption phase. This is aconsiderable advantage, and significantly enhances the detection offatty acids, ammonia and amines. However, it will be appreciated thatthis approach is not limited to the detection of these species, and noris it limited to the method of the present invention. Rather, theapproach of making conductimetric measurements in the desorption phasecan be employed as a general technique for detecting analytes usingconductimetric gas sensors which have a gas sensitive layer. Typically,a pulse of gas from the headspace is flowed over the sensor, and thedesorption phase commences once this pulse of gas has finished flowingover the sensor.

[0021] The conductimetric gas sensor or sensors may comprisesemiconducting organic polymer.

[0022] This method may further comprise the steps of:

[0023] performing a principal components analysis (PCA) of calibrationsamples to provide reference scores and reference loadings, which areused to construct a reference PCA map; and

[0024] projecting the output of the detector onto the reference PCA mapusing the reference loadings.

[0025] This approach permits very convenient and quick assessment ofwhether a sample is infected on the basis of simple assessment criteria.Furthermore, it is possible to calibrate the system and to performself-test protocols using this approach.

[0026] The reference PCA map may comprise a two dimensional map in whichone PCA axis is correlated to the presence of fatty acids and the otherPCA axis is correlated to the presence of ammonia and, optionally, aminespecies. Intensity data from the detector may be projected onto thereference PCA map so that position along the PCA axis is related to theconcentration in the headspace of the species which is correlated tothat PCA axis. In this way the intensity data can be related to theconcentration of marker species which in turn can be related to thenumber of infecting organisms. In particular, it is possible to observeif a threshold concentration has been crossed, allowing the correlationof detector output with the presence of infection to be made. It shouldbe noted that in the prior art, intensity data from electronic nosescomprising arrays of gas sensors are usually removed by normalisationbefore analysis such as PCA, so that concentration independent“fingerprints” can be obtained.

[0027] Methods in accordance with the invention will now be describedwith reference to the accompanying drawings, in which:

[0028]FIG. 1 is a schematic diagram of apparatus suitable foridentifying the presence of an infection in a liquid sample,

[0029]FIG. 2 shows sensor responses a) to acetic acid of one polymertype and b) to ammonia of another polymer type as a function of time;

[0030]FIG. 3 shows a PCA transformation;

[0031]FIG. 4 shows a PCA reference map;

[0032]FIG. 5 shows the calculation of projected PCA scores;

[0033]FIG. 6 is a graphical representation of a first discriminationcheck along the PC1 axis;

[0034]FIG. 7 is a graphical representation of a second discriminationcheck along the PC1 axis;

[0035]FIG. 8 is a graphical representation of a classification thresholdalong the PC1 axis;

[0036]FIG. 9 shows the classification of liquid samples, from dataprojected onto a classification map; and

[0037]FIG. 10 shows sample classification using PCA mapping.

[0038]FIG. 1 schematically depicts apparatus shown generally at 10, foruse with the method of the present invention. The apparatus comprises asample carousel 12 in which a number of sample vials can be mounted andmaintained at a constant temperature, for example 30° C. For simplicity,a single sample vial 14 is shown in FIG. 1. The vial 14 contains aliquid sample 16. Above the liquid sample 14 is a gaseous headpsace 18which contains inter alia volatile species emanating from the liquidsample 16. For reasons which are explained in more detail below, theliquid sample 16 is acidified before being introduced into the carousel12 so as to drive fatty acids present in the liquid sample into thegaseous phase and thus into the headspace 18.

[0039] The vial 14 has a septum 14 a thereon which is pierced by aneedle 20, the insertion of needle 20 into the vial 14 being performedautomatically by the apparatus 10. The needle 20 is of co-axial design,which permits a carrier gas (such as air, nitrogen or a noble gas) to beintroduced to vial 14 via one of the lumen of the needle 20. Gases inthe headspace 18 are entrained in the flow of carrier gas, which exitsthe vial 14 via the other lumen of the needle 20, and thereafter isflowed across a gas sensor array 22. In this way, the headspace 18 issampled by a gas detector 22, which in this embodiment is a gas sensorarray. It will be appreciated by the skilled reader that there are manyother ways in which the headspace might be coupled to a gas detector—forexample, carrier gas might be introduced to the vial 14 thorugh aconduit which protrudes into the liquid sample 16, thus “bubbling” thecarrier gas through the liquid sample 16, and exit through a separateaperture which is separated from the liquid sample 16. This is aso-called “sparging” technique. Additionally, the use of devices such asfilters and preconcentrators is feasible.

[0040] The gas sensor array 22 is selected so that it can detect fattyacids, in particular acetic acid, ammonia and, optionally, aminespecies. These species constitute the “marker” species which, it hasbeen found, can be indicative of infection.

[0041] The output of the gas sensor array 22 is monitored and analysedby control means 24 which comprise computer means or othermicroprocessor-based analysis means. The control means 24 can alsocontrol the operation of the carousel 12, the flow of carrier gas,washing and calibration procedures, and the manner in which the gassensor array 22 is operated or interrogated. However, it is quitepossible to transfer data from the control means 24 to, for example, aremote computer for analysis. In any event, some form of analysis meansis provided which is adapted to correlate the presence of the detectedfatty acids, ammonia and, optionally, amine species with the presence ofthe infection. In this way, the liquid sample 14 is screened for theinfection.

[0042] The method of the present invention has been used to screen urinesamples for urinary tract infections. Human urine is a highly complexmixture comprising many components and species of microorganisms. Someof the components of urine are volatile, and thus the headspaceassociated with a sample of urine is itself complex. It is known from WO95/33848 that microorganisms can produce volatile species which arecharacteristic of the microorganisms. What is not known from WO 95/33848is how, with a highly complex headspace associated with any urinesample, one can identify the presence of an infection in the urinesample from gases emanating from the sample.

[0043] There are a number of microorganisms implicated in urinary tractinfection, such as Proteus mirabilis, Staphylococcus aureus,Staphylococcus saprophyticus, Eschercia coli, Klebsiella pneumoniae andEnterrococcus faecalis. Surprisingly, a quite limited set of gaseous“marker” species have been found to be indicative of the presence ofurinary tract infection by these agents. The pH of the liquid sample islowered, typically to a pH of 2.0 or below, often to a pH of around 1.0,in order release fatty acids into the gaseous phase. Surprisingly, evenunder acidic conditions, it is still possible for ammonia (and volatileamine species) to be evolved in sufficient quantity to be useful as a“marker” species. In fact, the detection of ammonia (and/or volatileamines) is extremely important because such species are indicative ofinfection by Proteus mirabilis. It is believed that Proteus sp. remainsactive despite the acidification, and produces ammonia as a metabolite.The presence of ammonia neutralises to some extent the added acid, andthus the pH of samples producing ammonia is somewhat higher than that ofsamples which are not infected with Proteus sp. Ammonia is typicallyobserved by the gas detector at a pH of around 4 or greater. It ispossible to observe both ammonia and acetic acid signals at such pHs. Itshould be noted that it may be possible to detect additional markerspecies in order to provide improved detection or even to aid in theidentification of specific species.

[0044] Preparation of the liquid sample thus includes the addition of anacid, for example, HCl, in sufficient quantity to lower the pH to thedesired value. Optionally, a salt such as Na₂SO₄ can be added in orderto displace less soluable volatiles, in particular organic species, fromsolution and into the gaseous phase. Since the liquid samples can behighly acidic, often of a pH ca. 1 and often at a temperature above roomtemperature, proper selection of materials is very important. Nickel isa suitable metal for use in components such as a sampling needle(conventional metals such as stainless steel being too reactive). PTFEcan be used elsewhere. Backwashing between samples is advisable toprevent cross-contamination.

[0045] In a preferred embodiment, the gas detector is an array of gassensors, and in a particularly preferred embodiment the gas sensorscomprise semiconducting organic polymer gas sensors. However, inprinciple, other forms of gas detector might be employed, provided thatthey are sensitive to the marker species described above. As anindication of the sensitivities required, it is noted that a GC/MSanalysis performed by the Applicants of 98 samples of urine of which 50%were confirmed positive for bacteria using traditional culture andcolony counting methods, indicated that control samples were on averageassociated with a concentration of 3 ppm acetic acid, 6 ppm being thethreshold for false positives, and that the range of positives was from6-500 ppm, with an average value being about 100 ppm. Gas detectiontechniques which are candidates for use in the present invention includegas chromatography, mass spectrometry and spectroscopic techniques suchas IR spectroscopy. Other forms of gas sensor array might becontemplated, such as arrays of metal oxide sensors, SAW sensors, quartzresonators, “composite” sensors of the type described generally in U.S.Pat. No. 5,571,401, and arrays comprising mixtures thereof.

[0046] Embodiments of a preferred—but non-limiting-kind of gas detectorwill now be described, namely arrays of semiconducting organic polymergas sensors. As discussed above, the traditional approach with sucharrays is to employ a large number (typically twenty or more) ofdifferent sensors having different polymers and/or different dopantcounterions, thus producing an array in which the individual gas sensorsexhibit broad and overlapping sensitivities towards a range of differentgases. The same principle applies to other arrays of gas sensors, suchas metal oxide sensors. Devices of this type are commonly referred to as“electronic noses”.

[0047] In direct contrast, it has been found that screening forinfection according to the present invention can be advantageouslyperformed using an array which comprises a limited number of sensortypes, ie. sensors with physically different polymer/counterioncombinations. In one example, four types of selective conducting polymersensors have been developed and incorporated into a device. Two of theseare acid sensitive, one sensitive to ammonia, and the other sensitive toammonia and trimethyl amine. These four sensor types are incorporatedinto a 48 sensor array, comprising 12 sets of replicate sensors. Theprovision of 12 replicates of each sensor type permits signal averagingover a large number of sensors. Additionally, sets of replicate sensorsallows the array to function in the event that one or even more than onesensor in any given replicate set malfunctions.

[0048] The changes in resistance of each sensor type in response to avolatile sample are recorded with time, and are averaged for each sensortype over the array. It has been observed that it is possible toeliminate the effect of water vapour on the response of the sensors bychoosing a portion of the trace corresponding to the desorption phase ofthe experiment. With acetic acid as the analyte, it has been observedthat there is undershoot in the signal below the previous baseline (seeFIG. 2a). This effect is reproducible, is a function of concentration ofacetic acid, and is a parameter due to the type of materialsincorporated into the sensor. The time course is primarily dependent onthe sensor kinetics, but carrier flow and header geometry will also havean effect.

[0049]FIG. 2a shows a number of response profiles to acetic acid for asemiconducting organic polymer sensor against time. The baselineresponse is indicated at “A”. During the period of time indicated as“B”, the sensors are exposed to a pulse of gas comprising acetic acidentrained in a carrier gas. This can be regarded as an “adsorptionphase” during which there is nett adsorption of acetic acid—andwater—onto the sensors. After the gas pulse has finished, there is adesorption phase, or recovery phase, which is indicated as “C”, duringwhich there is a nett desorption of analyte from the sensors. It can beseen that the response becomes negative with respect to the baselineduring the recovery phase. With fatty acid analytes, signal averagedover the period C is a function of the concentration of acid present inthe headspace. The responses shown at “D” and “E” relate to (standard)wash and reference cycles, respectively.

[0050] It should be noted that generally similar responses are obtainedwhen the sensors are expected to ammonia (FIG. 2b), ie. there aredistinct baseline, adsorption and recovery phases. However, the responsein the recovery phase in this instance remains positive with respect tothe baseline. Measurements made during the recovery phase are alsosubstantially free from interferences from moisture.

[0051] Interference from moisture is a major limitation for a number ofgas sensing technologies which interrogate a gas sensitive layer of somekind upon which analytes—and water vapour—can reversibly adsorb.Semiconducting organic polymers are an example of such a gas sensitivelayer. The above described technique for rejecting interferring signalsdue to moisture is of broad significance—not only is the techniqueapplicable in the context of screening for urinary tract infection, itcan be utilised more widely in the detection of analytes per se.

[0052] It is believed that the displacement of the sensor response fromthe baseline during the recovery phase is a result of the analyte stillbeing bound at the polymer surface. As a result of interactions betweenthe bound analyte and the electronic structure of the polymer, thepolymer can be more doped (producing a negative response) or less doped(producing a positive response) than when the baseline measurements weremade. It is believed that water desorbs from the polymer surface veryrapidly during the recovery phase, and so most of the recovery phase issubstantially moisture free. However, these mechanisms are speculativein nature, and should not be regarded as a limiting one.

[0053] It should be noted that, whilst prior art semiconducting organicpolymer gas sensors generally show good sensitivity towards ammonia, ithas not previously been possible to detect fatty acids such as aceticacid at low concentrations using such gas sensors. The present inventionprovides new gas sensors which employ new semiconducting organicpolymers. With these polymers, high sensitivity towards fatty acids(such as acetic acid) and ammonia can be achieved.

[0054] The new materials have a bilayer structure with a baselayer ofpolypyrrole deposited chemically using ferric chloride as an oxidant.Different sensor types are manufactured by electrochemically depositingdifferent top layer polymers onto this baselayer. The four types ofsensors incorporated into the device described above use the followingmonomer/electrolyte combinations for the electrochemical depositionstage:

[0055] 1. 3-Hexanoylpyrrole/tetraethylammonium p-toluenesulponate

[0056] 2. 1-Octylpyrrole/tetrabutylammonium triflate

[0057] 3. 3-Dodecylpyrrole/Tetraethylammonium tetrafluoroborate

[0058] 4. 1-Dodecylpyrrole/Tetraethylammonium tetrafluoroborate

[0059] The 3-substituted monomers can be synthesised following themethod of Ruhe et al (Makromol, Chem., Rapid Commun. 10 (1989) 103). The1-substituted monomers can be synthesied following the method ofSantaniello et al (Synthesis, 1979, 617).

[0060] Further details of the polymerisation conditions and of thepreparation of polymer bilayers having a baselayer of polypyrrole can befound in the Applicant's earlier International Publication WO 96/00383.

[0061] Data Processing

[0062] An object of the invention is to produce a rapid screening systemfor urinary tract infection. The system is capable of making a decisionbased on the relative intensities of acetic acid and/or ammonia presentin the urine headspace. This has been greatly facilitated by a noveldata processing technique which is discussed below and which is based onprincipal components anslysis (PCA—see, for example, J E Jackson, JQual. Tech., 13(1) (1981)). It has been established that if a principalcomponents analysis of the intensity data from the highly orthogonalsensors is carried out, the distribution of points projected on a firstprincipal components axis PCA 1 is correlated to acetic acid, and thatthe points projected on a second principal components axis PCA 2 arecorrelated to ammonia. The distribution along either coordinate axis isalso a function of the concentration of the analyte in the headspace,and hence of the concentration of marker chemicals produced by themicroorganisms present in the sample. This thus gives a simple way ofassigning a threshold for deciding whether or not a sample is positiveor negative, based on user-defined clinical criteria. For example, 10⁵cfu's/ml or greater may be taken to constitute an infection (a cfu is acolony forming unit). In broad terms, the data processing comprisesusing calibration samples to establish a PCA “reference map”, and thenprojecting data obtained from enclosed samples onto this PCA referencemap in order to establish if these data are indicative of infection.

[0063] Data processing is described in more detail below, with referenceto various calibration and measurement process which are performed.

[0064] 1. Calibration

[0065] Calibration is a two-stage process:

[0066] 1. Run calibration standards to generate reference map, verifyresults and store PCA loadings information;

[0067] 2. Run calibration standards, project data on to reference map,verify results and calculate the classification thresholds.

[0068] In one example the array is calibrated using defined standardsconsisting of acetic acid (in concentrations of 3, 20 and 100 ppm) in0.1M HCl/20% Na₂SO₄, and ammonium hydroxide (10 ppm) in 0.01M NaOH. 1 mlsample volumes are used as above. Before each main experimental run,subsets of standards are run, each sample cycle lasting 20 minutes.

[0069] 1.a. Reference Map

[0070] The calibration data is transformed using Principal ComponentAnalysis (PCA) to characterise the instrument sensor responses for thecalibrants run, thus defining a two-dimensional mapping space on towhich all subsequent samples analysed can be projected. PCA decomposesthe original calibrant data matrix into a set of scores and loadingvectors, in which scores contain information of how samples relate toone another whilst the loadings show how variables relate to oneanother. This process is depicted in FIG. 3, and can be written as:

X=t×p ^(T)

[0071] where t denotes the scores, which are vectors of linearcombinations of sensor variables that describe the major trends in theoriginal data matrix X. The loadings, which are represented by p, are aset of orthonormal eigenvectors representing a new set of axes ontowhich the scores information is projected. In FIG. 3 T denotes thetranspose of a matrix. The result is a “reference map” which is shown inFIG. 4.

[0072] Projected scores (PC1 and PC2) can be calculated by multiplyingthe analysis results with the reference loadings calculated in thecalibration step. This process is depicted in FIG. 5.

[0073] 1.b. Discrimination Check

[0074] In the following discussion, USB1k is the 3 ppm acetic acidstandard referred to above, US1 is the 20 ppm acetic acid standardreferred to above, US2 is the 100 ppm acetic acid standard referred toabove, and US3 is the 10 ppm ammonium hydroxide standard referred toabove.

[0075] Discrimination Check 1: A system check is performed on thecalibration data to ensure that there is no overlap between the sampledistributions for each of the standards (US1, US3) and the USB1k at the97.5% confidence interval for the mean of each standard. FIG. 6 depictssuch a check for the US1 samples along the PC1 axis.

[0076] In FIG. 6, Δ₁ is the degree of separation between the populationdistribution of US1 and USB1k sample responses along the PC1 axis at the97.5% confidence level. The following condition must be satisfied toshow that the population distribution between the standards areseparated:

|Mean US1_(PC1)−Mean USB1k _(PC1)|

2×(SD US1_(PC1) +SD USB1k _(PC1))

Mean US3_(PC2)−Mean USB1k _(PC2)|

2×(SD US3_(PC2) +SD USB1k _(PC2))

[0077] This corresponds to Δ₁

0.

[0078] Discrimination Check 2: Once satisfied that there is no overlapbetween each of the separate clusters, a second check is performed toensure that the level of discrimination between the standards is above aminimum acceptable discrimination threshold (DT) value, such that:

Mean US1_(PC1)−Mean USB1k _(OC1)

|

DT

Mean US3_(PC2)−Mean USB1k _(PC2)

|

DT

[0079] This check is depicted in FIG. 7.

[0080] 1.c. Classification Thesholds

[0081] The classification thesholds are defined as:

CT1=(Mean US1_(PC1)−Mean USB1k _(PC1))/2 (along the PC1 axis)

CT2=(Mean US3_(PC2)−Mean USB1k _(PC2))/2 (along the PC2 axis)

[0082] The classification theshold CT1 (along the PC1 axis) is depictedin FIG. 8.

[0083] 2. Classification Map

[0084] The information provided by the calibration processes is used toconstruct a “classification map”, a representation of which is shown inFIG. 9. The classification map can then be used for sensor check andclassifying clinical samples. Samples that lie within the shaded regionare then classified as negatives while those that are projected outsidethe shaded region are classified as positive samples.

[0085] A summary of these data processing steps is shown in FIG. 10, inwhich Δ_(i) is the separation between each sample population (i=1,2) andCT is the classification threshold along each principal component axis.The shaded region 100 is the region of the PCA map representating anegative UT1 classification.

[0086] Variants to the scheme described above would suggest themselvesto the skilled reader. For example, samples may be separated andclassified using Mahalanobis distance measure. In principle, more thantwo principal components might be used to construct the reference mapand classification map. Such an approach may not be of great advantagein the context of the technique for detecting urinary tract infectiondiscussed above. However, the data processing principles discussed abovemay be applicable to the analysis of gas sensors in other applicationareas and the approach may even be applicable beyond the field of gassensors, perhaps to the analysis data from combinations of other kindsof sensor, or to multivariate data analysis per se.

EXAMPLE

[0087] Sterile pooled human urine (PHU), cultures of common urinarypathogens in PHU and 340 unselected clinical urine specimens (CUS) wereanalysed using the apparatus described above, and using conventionalsemi-quantitative plate culture method and the results compared.

[0088] Urine samples were analysed in the following way. 1 ml of urinewas transferred to a 22 ml vial containing 0.4 ml 1 M HCl and 200 mg ofsodium sulphate. The 22 ml sample vial was capped with a PTFE-linesilicone septum. The vial was placed in a carousel as shown in FIG. 1and allowed to equilibrate at 30° C. to allow a consistent generation ofsample headspace. The apparatus then automatically inserted a needlethrough the sample vial septum, in order to analyse the headspace.Nitrogen gas at 50% relative humidity was introduced above the surfaceof the urine via the inner lumen of the coaxial needle. The sampleheadspace was sampled through the outer lumen of the needle, and flowedover the sensors at a flow rate of ca. 60 ml min−1. The sensors wereallowed to recover before humid nitrogen gas was passed over the sensorsfor a 4 minute “wash”. The resistance of each of the sensors wasmeasured during the recovery period (typically between 220 and 240seconds after sampling), and the change (ΔR) from the initial resistance(base resistance R), was calculated. The needle was then removed, thecarousel moved the next sample into position, and the process wasrepeated. Each PHU specimen was analysed four times and the resultsrecorded as the mean of the four replicates.

[0089] Results PHU containing

10⁵ cfu/ml of E. coli, K. pneumoniae, P. mirabilis, S. aureus, S.saprophyticus or E. faecalis were readily distinguished from sterilecontrols, demonstrating the utility of this method: 76/340 CUS (22%)were positive by conventional culture. 53% of positives contained E.coli, 11% E. faecalis, 8% Klebsiella spp., 5% Pseudomonas spp., 3% GroupB Streptococci, 1% Proteus spp., 1% Candida spp. and 18% mixedorganisms. The sensitivity specificity, NPV and PPV values of theclassification were 85.5%, 89.0%, 95.5% and 69.1% respectively. Therewere 11 false negatives and 29 false positives. The tendency of thesystem to over report false positives rather than false negatives isdesirable in a screening system since all positive specimens are furtherinvestigated by conventional methods.

1. A method for detecting the presence of an infection in a liquidsample comprising the steps of: lowering the pH of the liquid sample soas to drive fatty acids present in the liquid sample to the gaseousphase; detecting fatty acids, ammonia and, optionally amine speciespresent as gases in a headspace associated with the liquid sample usinga detector which is sensitive to the presence of fatty acids, ammoniaand, optionally, amine species; and correlating the presence of detectedfatty acids, ammonia and, optionally, amine species with the presence ofthe infection.
 2. A method according to claim 1 in which the liquidsample is, or is derived from, a body fluid.
 3. A method according toclaim 2 in which the infection is a urinary tract infection and theliquid sample is, or is derived from, a urine sample.
 4. A methodaccording to claim 3 in which infection by any of the microorganismsProteus mirabilis, Staphylococcus aureus, Staphylococcus saprophyticus,Eschericia coli and Klebsiella pneumoniae is detectable.
 5. A methodaccording to claim 1 in which the detector comprises an array of gassensors.
 6. A method according to claim 5 in which the array comprisesgas sensors having semiconducting organic polymer as a gas sensitivelayer.
 7. A method according to claim 1 in which the detector issensitive to gaseous acetic acid, and in which the presence of aceticacid, ammonia and, optionally amine species is correlated with thepresence of the infection.
 8. A method according to claim 1 in which thedetector comprises semiconducting organic polymer.
 9. A method accordingto claim 1 in which the detector comprises at least one conductimetricgas sensor having a gas sensitive layer onto which gases adsorb anddesorp, and in which analytes are detected by: exposing the gas sensorto the headspace, thereby allowing the adsorption of analytes present inthe headspace onto the gas sensitive layer; and making conductimetricmeasurements of the sensor during a desorption phase in which there isnett desorption of analyte from the gas sensitive layer.
 10. A methodaccording to claim 9 in which the conductimetric gas sensor or sensorscomprise semiconducting organic polymer.
 11. A method according to claim1 in which: a principal component analysis (P CA) of calibration samplesis performed to provide reference scores and reference loadings whichare used to construct a reference PCA map; and the output of thedetector is projected onto the reference PCA map using the referenceloadings.
 12. A method according to claim 11 in which the reference PCAmap comprises a two dimensional map in which one PCA axis is correlatedto the presence of fatty acids and the other PCA axis is correlated tothe presence of ammonia and, optionally, amine species.
 13. A methodaccording to claim 12 in which intensity data from the detector areprojected onto the reference PCA map so that position along a PCA axisis related to the concentration in the headspace of the species which iscorrelated to that PCA axis.